• 대한산업공학회지
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• 제25권1호
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• pp.130-140
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• 1999

This paper deals with a priority queueing model in an ATM system. Two types of customers are considered. Type-1 customers have push-put priority over type-2 customers. Type-1 customers can enter the service only when the number of type-2 customers is less than a threshold T. We derive the joint probability of the number of customers in the buffer, the mean waiting time, and the loss probabilities of each type. We also propose an optimal control policy that satisfies a given quality of service.

• 산업경영시스템학회지
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• 제24권66호
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• pp.11-18
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• 2001

In this paper, we analyze an M/G/1 two-phase gated service model with threshold. We consider compound Poison arrival Process and general service time, where the server fives two different modes of services in order, batch and individual services. Server starts his service when the number of arrived customers reaches the predetermined threshold . We find the PGF of the number of customers in system and LST of waiting time, with which we obtain the means of them.

• 대한산업공학회지
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• 제16권1호
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• pp.107-114
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• 1990

A queueing system with compound Poisson arrival and server vacation is analyzed by including supplementary variables. We consider a vacation system in which the server leaves for a vacation as soon as the system empties. When he returns, if no customer is waiting for service, he waits until a group of customers arrive and then begins to serve. We obtain the system size distribution and the waiting time distribution. Additional performance measures will be also considered.

• 대한산업공학회지
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• 제27권4호
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• pp.374-378
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• 2001

We present a discrete-time version of the distributional Little's law, of which the continuous-time version is well known. Then we extend it to the queue in which two or more customers may depart at the same time. As a demonstration, we apply this law to various discrete-time queues such as the standard Geom/G/1 queue, the Geom/G/1 queue with vacations, the multi-server Geom/D/c queue, and the bulk-service Geom/$G^b$/1 queue. As a result, we obtain the probability generating functions of the numbers in system/queue and the waiting times in system/queue for those queues.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.940-943
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• 2014

현재 기업이나 관공서 등에서 고객들은 대기표를 발권한 후 대기하며 시간을 소비하는 불편함을 겪고 있다. 이를 개선하고자 본 논문은 스마트폰과 연동하여 실시간 대기인원현황 알림서비스를 제공하는 새로운 대기표발권시스템 설계를 제안한다. 본 시스템의 설계를 위하여 발권기에 NFC 태그를 추가하여 대기정보를 입력한다. 그리고 대기표를 사용하는 기업 및 관공서들의 정보를 통합적으로 제공하고 관리하여 사용자들의 편의성을 증대시킨다. 따라서 본 시스템을 활용하면 기존 발권 시스템을 사용했을 때보다 대기시간을 효율적으로 사용할 수 있고, 발권종이를 사용하지 않음으로써 비용절감과 환경보호 효과까지 있을 것으로 보인다. 또한 애플리케이션으로 대기표 발권 취소 기능을 통해 업무 프로세스를 개선하는데 활용할 수 있다.

• 한국병원경영학회지
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• 제8권2호
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• pp.49-69
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• 2003

This study purported to evaluate the performance of the appointment system for outpatients in primary care dental clinic. The data of patients' time flow for 1,245 patients in Y Dental Clinic were collected for one month in 2002 and then analyzed. Specifically, the time periods of treatment and patients' waiting as well as rates of appointment and it's failure are estimated. The accuracy of expected treatment time period was also evaluated. The results showed that 72% of patients visited the clinic with appointments, and only 56% kept their appointments. The patient's waiting time period turned out to be 11 minutes in Y clinic. The expected treatment time period is turned out to be very important because they influence significantly on patient's waiting time period. Practically, the expected treatment time period should be overestimated about 9 minutes in general, and the characteristics of dentist, each patient's diagnosis and age need to be especially considered. Hospitals and clinics also need to make the systematic and detailed critical pathways for a variety of patient cases by analyzing the patients' treatment pattern. With the improved appointment systems, healthcare institutions will approach the goal of effective and efficient management of the institution and also satisfy their customers.

• 산업경영시스템학회지
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• 제25권5호
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• pp.31-38
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• 2002

In this paper, we model a two-server queueing system with priority, to which we put a restriction on the number of servers for each customer class. customers are divided into two different classes. Class 1 customers have non-preemptive priority over class 2 customers. They are served by both servers when available but class 2 customers are served only by a designated server. We use a method of generating function depending on the state of servers. We find the generating function of the number of customers in queue, server utilization, mean queue length and mean waiting time for each class of customers.

• 대한수학회지
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• 제35권3호
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• pp.503-525
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• 1998

In the theory of retrial queues it is usually assumed that the flow of primary customers is Poisson. This means that the number of independent sources, or potential customers, is infinite and each of them generates primary arrivals very seldom. We consider now retrial queueing systems with a homogeneous population, that is, we assume that a finite number K of identical sources generates the so called quasi-random input. We present a survey of the main results and mathematical tools for finite source retrial queues, concentrating on M/G/1//K and M/M/c//K systems with repeated attempts.

• 대한산업공학회지
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• 제12권1호
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• pp.63-71
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• 1986

In the organization with a hierarchical network queue structure a production function is derived whose input factors are the numbers of servers at nodes and output is the number of served customers. Its useful properties are investigated. Using this production function, the contributions of servers to the number of served customers are studied. Also given an expected waiting time in the system for each customer, the optimal numbers of servers at nodes are obtained minimizing a cost function.

• 대한산업공학회지
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• 제25권1호
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• pp.141-149
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• 1999

In this paper, we consider multiple-class queueing systems in which the server starts a set-up as soon as the number of customers in the "start-up class" reaches threshold N. After the set-up the server starts his service. We obtain the Laplace-Stieltjes transform and the mean of the waiting times of each class of customers for FCFS and non-preemptive priority disciplines.